The use of items and item parcels in nonlinear structural equation models

Karina Rdz-Navarro,Rodrigo A Asún

doi:10.5964/meth.2305

Abstract

Nonlinear structural equation models within the frequentist framework were developed to work with continuous items. Applied researchers who usually work with Likert-type items choose between two strategies to estimate such models: treat items as continuous variables or create item parcels. Two Monte Carlo studies were conducted to evaluate the effects of each strategy on estimates and Type I errors for models with interaction and quadratic effects estimated using LMS. The first study evaluated the effect of asymmetry type and item quantity. The second assessed the use of item parcels and parcel configuration under equivalent conditions. Results reveal that treating items as continuous variables is not problematic when item categories are symmetrical or have opposite-direction asymmetries; however, meaningful parameter bias and increased Type I errors are produced in the case of same-direction asymmetry. Use of parcels does not overcome these problems. The results are discussed to provide recommendations for applied researchers.

Highlights

Nonlinear structural equation models within the frequentist framework were developed to work with continuous items
The present study addresses this gap by evaluating the impact of treating items as continuous indicators and creating item parcels to estimate nonlinear structural models using the Latent Moderated Structural equation method (LMS) method
A set of exploratory simulations conducted to cross-validate these results enabled us to establish that using items with three, four or seven response categories generates results equivalent to those reported here when item asymmetry levels are equivalent to those examined here

Summary

Introduction

Nonlinear structural equation models within the frequentist framework were developed to work with continuous items. Applied researchers who usually work with Likert-type items choose between two strategies to estimate such models: treat items as continuous variables or create item parcels. Two Monte Carlo studies were conducted to evaluate the effects of each strategy on estimates and Type I errors for models with interaction and quadratic effects estimated using LMS. The first study evaluated the effect of asymmetry type and item quantity. The second assessed the use of item parcels and parcel configuration under equivalent conditions. Results reveal that treating items as continuous variables is not problematic when item categories are symmetrical or have opposite-direction asymmetries; meaningful parameter bias and increased Type I errors are produced in the case of same-direction asymmetry. The results are discussed to provide recommendations for applied researchers

Findings

Discussion

Conclusion